RISK ESTIMATION AND MODIFIER GENES IN INHERITED CANCER

描述（改编自研究者摘要）：在过去十年中， 在定位和鉴定特定基因方面已经取得了进展， BRCA 1和p16在改变时可显著增加易感性， 相对常见的癌症。虽然这些基因的变异显然 增加癌症的风险在各种解剖部位，有争议 这些风险的严重性。基于人群研究的风险 得出的风险估计值低于 一个大家庭或一系列多个高风险家庭。是否这些 差异反映了用于风险估计的方法中的固有偏差，或 代表了在高危家庭中修饰基因座分离的影响， 不明显估计基因效应的统计方法相对较少， 不发达。此外，还没有研究检查 在总体背景下定位假设修饰基因座的可行性 基因组搜索本项目旨在研究效率和偏见相关 采用各种抽样设计和统计方法估计癌症 这些基因的风险。蒙特-卡罗模拟和现有数据集 包含上述三种方法的方法将用于 评价方法多种多样。a）测试效果的几种设计 关于特定候选基因座的风险修饰; B）检测 剩余遗传效应;以及c）检查不同抽样的功效 设计全基因组筛选定位修饰基因座也将是 考察

DESCRIPTION (Adapted from investigator's abstract): During the past decade, progress has been made in localizing and identifying specific genes such as BRCA1 and p16 which when altered can confer a markedly increased susceptibility to relatively common cancers. Although variations at these genes apparently increase risk of cancer at a variety of anatomical sites, there is controversy about the magnitude of these risks. Risks derived from population-based studies have produced lower estimates of risk than those estimated from studies of single large families or series of multiple high-risk families. Whether these differences reflect inherent biases in the methods used for risk estimation or represent the effects of modifying loci segregating in high-risk families is not obvious. Statistical methods for estimation of gene effects are relatively underdeveloped. Additionally, there have been no studies that examine the feasibility of mapping hypothesized modifier loci in the context of a total genome search. This project seeks to examine the efficiency and bias associated with various sampling designs and statistical methods for estimation of cancer risks due to such genes. Monte-Carlo simulation and existing datasets encompassing the three approaches described above will be used for the evaluation of a variety of methods. Several designs for a) testing the effect on risk modification of specific candidate loci; b) detecting the presence of residual genetic effects; and c) examining the power of different sampling designs for genome-wide screens to localize modifier loci also will be examined.